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Computational fluid dynamics of gas-fueled large-bore spark ignition engines with pre-chamber ignition can speed up the design process of these engines provided that 1) the reliability of the results is not affected by poor meshing and 2) the time cost of the meshing process does not negatively compensate for the advantages of running a computer simulation. In this work a flame propagation model that runs with arbitrary hybrid meshes was developed and coupled with the KIVA4-MHI CFD solver, in order to address these aims. The solver follows the G-Equation level-set method for turbulent flame propagation by Tan and Reitz, and employs improved numerics to handle meshes featuring different cell types such as hexahedra, tetrahedra, square pyramids and triangular prisms. Detailed reaction kinetics from the SpeedCHEM solver are used to compute the non-equilibrium composition evolution downstream and upstream of the flame surface, where chemical equilibrium is instead assumed.

Engine experiments and multi-dimensional modeling were used to explore the effects of isobutanol as both the high and low reactivity fuels in Reactivity Controlled Compression Ignition (RCCI) Combustion. Three fuel combinations were examined; EEE/diesel, isobutanol/diesel, and isobutanol/isobutanol+DTBP (di-tert butyl peroxide). In order to assess the relative performance of the fuel combinations of interest under RCCI operation, the engine was operated under conditions representative of typical low temperature combustion (LTC). A net load of 6 bar indicated mean effective pressure (IMEP) was chosen because it provides a wide operable range of equivalence ratios and combustion phasings without excessively high peak pressure rise rates (PPRR). The engine was operated under various intake pressures with global equivalence ratios from 0.28-0.36, and various combustion phasings (defined by 50% mass fraction burned-CA50) from about 1.5 to about 10 deg after top dead center (ATDC).

The incorporation of detailed chemistry models in internal combustion engine simulations is becoming mandatory as local, globally lean, low-temperature combustion strategies are setting the path towards a more efficient and environmentally sustainable use of energy resources in transportation. In this paper, we assessed the computational efficiency of a recently developed sparse analytical Jacobian chemistry solver, namely ‘SpeedCHEM’, that features both direct and Krylov-subspace solution methods for maximum efficiency for both small and large mechanism sizes. The code was coupled with a high-dimensional clustering algorithm for grouping homogeneous reactors into clusters with similar states and reactivities, to speed-up the chemical kinetics solution in multi-dimensional combustion simulations.